Scripts Folder

failureMechanism.py

The failureMechanism.py script is a Fuzzy Logic script that predicts the failure mechanism involved in a work history event. The failureMechanism.py script can be used in a Classifier node in a cognition so that historic, transactional data can be properly classified.

Note: You should consider first identifying which work history events should be defined as failures before using failureMechanism.py. When used on all work history events, failureMechanism.py will provide a prediction regardless of the failure classification of the work history event.

The failureMechanism.py script uses the following standard lists:

• failure_mechanism: provides valid values for classification predictions.
• brokenwords: provides a list of important words to identify during text cleaning. Due to constraints in legacy CMMS systems, words can appear to the script to be broken in the middle with a space. This list identifies potentially broken words that need to be modified and used.
• contraction: provides a list of contractions that are modified for consistency during text cleaning.
• stopwords: provides a list of words to remove during text cleaning.

For best results when testing or using failureMechanism.py, create a query or dataset that includes as many of the following fields as possible:

• Work history event short description
• Work history event long description
• Failure mechanism description
• Failure mode description

The Fuzzy Logic Template script is the template Fuzzy Logic script that is used to create new Fuzzy Logic scripts.

IMPORTANT: Do not modify the contents of this script.

The isAFailure.py script is a Machine Learning script that predicts if a work history event represents a failure as defined by ISO 14224: 2006. The isAFailure.py script can be used in a Classifier node in a cognition so that historic, transactional data can be properly classified.

The isAFailure.py script uses the following standard lists:

• failure: provides valid values for classification predictions.
• brokenwords: provides a list of important words to identify during text cleaning. Due to constraints in legacy CMMS systems, words can appear to the script to be broken in the middle with a space. This list identifies potentially broken words that need to be modified and used.
• contraction: provides a list of contractions that are modified for consistency during text cleaning.
• stopwords: provides a list of words to remove during text cleaning.

The isAFailure.py script includes anonymized training data from GE Digital's Asset Answers database. The training data includes features from the following fields:

• Work history event short description
• Failure mode description
• Priority description

When testing, using, or further training isAFailure.py, create a query or dataset that includes data with similar features.

The Machine Learning Template script is the template Machine Learning script that is used to create new Machine Learning scripts.

IMPORTANT: Do not modify the contents of this script.

The maintainableItem.py script is a Fuzzy Logic script that predicts the maintainable item involved in a work history event. The maintainableItem.py script can be used in a Classifier node in a cognition so that historic, transactional data can be properly classified

The maintainableItem.py script uses the following standard lists:

• maintainable_item: provides valid values for classification predictions.
• brokenwords: provides a list of important words to identify during text cleaning. Due to constraints in legacy CMMS systems, words can appear to the script to be broken in the middle with a space. This list identifies potentially broken words that need to be modified and used.
• contraction: provides a list of contractions that are modified for consistency during text cleaning.
• stopwords: provides a list of words to remove during text cleaning.

For best results when testing or using maintainableItem.py, create a query or dataset that includes as many of the following fields as possible:

• Work history event short description
• Work history event long description
• Maintainable item description